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Results: 1 to 20 of 151

Similar articles for PubMed (Select 24056838)

1.

Integrated gene co-expression network analysis in the growth phase of Mycobacterium tuberculosis reveals new potential drug targets.

Puniya BL, Kulshreshtha D, Verma SP, Kumar S, Ramachandran S.

Mol Biosyst. 2013 Nov;9(11):2798-815. doi: 10.1039/c3mb70278b.

PMID:
24056838
2.

Arabidopsis gene co-expression network and its functional modules.

Mao L, Van Hemert JL, Dash S, Dickerson JA.

BMC Bioinformatics. 2009 Oct 21;10:346. doi: 10.1186/1471-2105-10-346.

4.

Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.

Colijn C, Brandes A, Zucker J, Lun DS, Weiner B, Farhat MR, Cheng TY, Moody DB, Murray M, Galagan JE.

PLoS Comput Biol. 2009 Aug;5(8):e1000489. doi: 10.1371/journal.pcbi.1000489. Epub 2009 Aug 28.

5.
6.

Transcriptomic and phylogenetic analysis of a bacterial cell cycle reveals strong associations between gene co-expression and evolution.

Fang G, Passalacqua KD, Hocking J, Llopis PM, Gerstein M, Bergman NH, Jacobs-Wagner C.

BMC Genomics. 2013 Jul 5;14:450. doi: 10.1186/1471-2164-14-450.

7.

Mycobacterium tuberculosis gene expression profiling within the context of protein networks.

Rachman H, Strong M, Schaible U, Schuchhardt J, Hagens K, Mollenkopf H, Eisenberg D, Kaufmann SH.

Microbes Infect. 2006 Mar;8(3):747-57. Epub 2006 Jan 18.

PMID:
16513384
8.

The Mycobacterium tuberculosis regulatory network and hypoxia.

Galagan JE, Minch K, Peterson M, Lyubetskaya A, Azizi E, Sweet L, Gomes A, Rustad T, Dolganov G, Glotova I, Abeel T, Mahwinney C, Kennedy AD, Allard R, Brabant W, Krueger A, Jaini S, Honda B, Yu WH, Hickey MJ, Zucker J, Garay C, Weiner B, Sisk P, Stolte C, Winkler JK, Van de Peer Y, Iazzetti P, Camacho D, Dreyfuss J, Liu Y, Dorhoi A, Mollenkopf HJ, Drogaris P, Lamontagne J, Zhou Y, Piquenot J, Park ST, Raman S, Kaufmann SH, Mohney RP, Chelsky D, Moody DB, Sherman DR, Schoolnik GK.

Nature. 2013 Jul 11;499(7457):178-83. doi: 10.1038/nature12337. Epub 2013 Jul 3.

9.

Transcriptional regulation of multi-drug tolerance and antibiotic-induced responses by the histone-like protein Lsr2 in M. tuberculosis.

Colangeli R, Helb D, Vilchèze C, Hazbón MH, Lee CG, Safi H, Sayers B, Sardone I, Jones MB, Fleischmann RD, Peterson SN, Jacobs WR Jr, Alland D.

PLoS Pathog. 2007 Jun;3(6):e87.

10.

Understanding network concepts in modules.

Dong J, Horvath S.

BMC Syst Biol. 2007 Jun 4;1:24.

11.

Mycobacterium tuberculosis interactome analysis unravels potential pathways to drug resistance.

Raman K, Chandra N.

BMC Microbiol. 2008 Dec 23;8:234. doi: 10.1186/1471-2180-8-234.

12.

Incorporating motif analysis into gene co-expression networks reveals novel modular expression pattern and new signaling pathways.

Ma S, Shah S, Bohnert HJ, Snyder M, Dinesh-Kumar SP.

PLoS Genet. 2013;9(10):e1003840. doi: 10.1371/journal.pgen.1003840. Epub 2013 Oct 3.

13.

Differential producibility analysis (DPA) of transcriptomic data with metabolic networks: deconstructing the metabolic response of M. tuberculosis.

Bonde BK, Beste DJ, Laing E, Kierzek AM, McFadden J.

PLoS Comput Biol. 2011 Jun;7(6):e1002060. doi: 10.1371/journal.pcbi.1002060. Epub 2011 Jun 30.

14.

Contribution of microarray data to the advancement of knowledge on the Mycobacterium tuberculosis interactome: use of the random partial least squares approach.

Mazandu GK, Opap K, Mulder NJ.

Infect Genet Evol. 2011 Jun;11(4):725-33. doi: 10.1016/j.meegid.2011.04.012. Epub 2011 Apr 14.

PMID:
21514402
15.

Identifying vulnerable pathways in Mycobacterium tuberculosis by using a knockdown approach.

Carroll P, Faray-Kele MC, Parish T.

Appl Environ Microbiol. 2011 Jul;77(14):5040-3. doi: 10.1128/AEM.02880-10. Epub 2011 Jun 3.

16.

Microarray analysis of efflux pump genes in multidrug-resistant Mycobacterium tuberculosis during stress induced by common anti-tuberculous drugs.

Gupta AK, Katoch VM, Chauhan DS, Sharma R, Singh M, Venkatesan K, Sharma VD.

Microb Drug Resist. 2010 Mar;16(1):21-8. doi: 10.1089/mdr.2009.0054.

PMID:
20001742
17.

Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets.

Vashisht R, Bhat AG, Kushwaha S, Bhardwaj A; OSDD Consortium, Brahmachari SK.

J Transl Med. 2014 Oct 11;12:263. doi: 10.1186/s12967-014-0263-5.

18.

Genetic diversity and striatal gene networks: focus on the heterogeneous stock-collaborative cross (HS-CC) mouse.

Iancu OD, Darakjian P, Walter NA, Malmanger B, Oberbeck D, Belknap J, McWeeney S, Hitzemann R.

BMC Genomics. 2010 Oct 19;11:585. doi: 10.1186/1471-2164-11-585.

19.

Low degree metabolites explain essential reactions and enhance modularity in biological networks.

Samal A, Singh S, Giri V, Krishna S, Raghuram N, Jain S.

BMC Bioinformatics. 2006 Mar 8;7:118.

20.

Differential network expression during drug and stress response.

Cabusora L, Sutton E, Fulmer A, Forst CV.

Bioinformatics. 2005 Jun 15;21(12):2898-905. Epub 2005 Apr 19.

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